The cost of digital storage for music is decreasing while Internet music services are becoming more prevalent. Accordingly, people are increasingly enjoying music obtained from Internet music services and stored on high-capacity portable players. And, as more people are acquiring music collections, the music collections are becoming larger, ranging from hundreds of songs to tens of thousands of songs. In addition, digital music production tools have made music creation easier and less-expensive. As a result, many new and lesser known artists are dramatically expanding the universe of recorded music that is available to choose from.
These trends make the ability to efficiently browse music collections and particularly, large collections, increasingly important. For example, a person may wish to browse their own music collection or may wish to discover songs they like from an unknown music collection. Or a music service provider may wish to provide improved tools that allow its customers to browse the service provider's collection of music.
Known methods of browsing music include websites that offer music for sale and which allow a person to play samples of songs. However, this can be somewhat tedious in that the person is typically required to manually select the desired artist, album and song from a large collection offered for sale. Collaborative filtering is a method of inferring what a particular person may like from a partial list of that person's likes and the tastes of many people. Collaborative filtering does not work well for new and lesser known artists due to lack of required information from many people.